TY -的A2 Versaci马里奥盟——Ghozia艾哈迈德·阿提亚盟——贾迈勒盟——不,Emad AU - El-Fishawy,纳瓦尔PY - 2020 DA - 2020/12/24 TI -智能超出学习:上下文感知的人工智能系统的视频理解SP - 8813089六世- 2020 AB -理解视频文件是一项非常具有挑战性的任务。目前的视频理解技术依赖于深度学习，但所获得的结果缺乏真正可信的意义。深度学习从大数据中识别模式，导致深度特征抽象，而不是深度理解。深度学习试图通过分析多媒体产品的内容来理解它。我们不能仅仅通过分析多媒体文件的内容来理解它的语义。场景中发生的事件的意义来自于包含它们的上下文。一个尖叫的孩子可能是被威胁吓到了，或者是被一个可爱的礼物吓到了，或者只是在后院玩耍。人工智能是一个复杂的过程，超越了学习。在本文中，我们将讨论人工智能作为一个过程的异质性，包括固有知识、近似和上下文感知。我们提出了一种上下文感知的视频理解技术，使机器智能到足以理解视频流背后的信息。 The main purpose is to understand the video stream by extracting real meaningful concepts, emotions, temporal data, and spatial data from the video context. The diffusion of heterogeneous data patterns from the video context leads to accurate decision-making about the video message and outperforms systems that rely on deep learning. Objective and subjective comparisons prove the accuracy of the concepts extracted by the proposed context-aware technique in comparison with the current deep learning video understanding techniques. Both systems are compared in terms of retrieval time, computing time, data size consumption, and complexity analysis. Comparisons show a significant efficient resource usage of the proposed context-aware system, which makes it a suitable solution for real-time scenarios. Moreover, we discuss the pros and cons of deep learning architectures. SN - 1687-5265 UR - https://doi.org/10.1155/2020/8813089 DO - 10.1155/2020/8813089 JF - Computational Intelligence and Neuroscience PB - Hindawi KW - ER -